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Gemini 2.0 Flash-Lite vs Gemma 3n E4B
Comprehensive side-by-side LLM comparison
Gemini 2.0 Flash-Lite leads with 2.3% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
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Gemini 2.0 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in MATH (86.8%), FACTS Grounding (83.6%), Global-MMLU-Lite (78.2%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.
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Gemma 3n E4B is a multimodal language model developed by Google. It achieves strong performance with an average score of 64.6% across 11 benchmarks. It excels particularly in ARC-E (81.6%), BoolQ (81.6%), PIQA (81.0%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.
4 months newer
Gemini 2.0 Flash-Lite
2025-02-05
Gemma 3n E4B
2025-06-26
Performance Metrics
Context window and performance specifications
Average performance across 24 common benchmarks
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Gemini 2.0 Flash-Lite
Average Score:31.9%(+2.3%)
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Gemma 3n E4B
Average Score:29.6%
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Knowledge Cutoff
Training data recency comparison
Gemini 2.0 Flash-Lite
2024-06-01
Gemma 3n E4B
2024-06-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Gemini 2.0 Flash-Lite
1 providers
Throughput: 85 tok/s
Latency: 0.7ms
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Gemma 3n E4B
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Gemini 2.0 Flash-Lite
Avg Score:31.9%(+2.3%)
Providers:1
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Gemma 3n E4B
Avg Score:29.6%
Providers:0